DocumentCode :
2822405
Title :
Radar phase-coded waveform design using MOEAs
Author :
Stringer, Jeremy ; Lamont, Gary ; Akers, Geoffrey
Author_Institution :
Dept. of Electr. & Comput. Eng., Air Force Inst. of Technol., Dayton, OH, USA
fYear :
2012
fDate :
10-15 June 2012
Firstpage :
1
Lastpage :
8
Abstract :
This study applies the NSGA-II, SPEA2, and MOEA/D Multi-Objective Evolutionary Algorithms (MOEAs) to the radar phase coded waveform design problem. The MOEAs are used to generate a series of radar waveform phase codes that have excellent range resolution and Doppler resolution capabilities, while maintaining excellent autocorrelation properties. The study compares the ability of NSGA-II, SPEA2, and MOEA/D to generate a Pareto front of phase code solutions, and then improve upon the quality of the solutions while maintaining a sufficient diversity of available radar phase codes. Results demonstrate that for solving moderate to large instances of the radar phase code problem all three MOEAs generate a diverse set of Pareto optimal radar phase codes. The phase codes generated by NSGA-II have overall better autocorrelation properties than those generated by SPEA2 and MOEA/D, however, all three MOEAs produce useable phase codes.
Keywords :
Pareto optimisation; genetic algorithms; phased array radar; radar resolution; Doppler resolution; MOEA/D; NSGA-II; Pareto front; Pareto optimal radar phase codes; SPEA2; autocorrelation property; multiobjective evolutionary algorithm; radar phase-coded waveform; range resolution; Correlation; Doppler effect; Doppler radar; Measurement; Signal to noise ratio; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1510-4
Electronic_ISBN :
978-1-4673-1508-1
Type :
conf
DOI :
10.1109/CEC.2012.6256554
Filename :
6256554
Link To Document :
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